Authors:
Hao Chen
and
Hesham A. Rakha
Affiliation:
Charles E. Via, Jr. Department of Civil and Environmental Engineering, Virginia Tech Transportation Institute, Virginia Polytechnic Institute and State University, 3500 Transportation Research Plaza, Blacksburg, VA 24061, U.S.A.
Keyword(s):
Eco-driving, Large-scale Traffic Network, Vehicle Engine Type, Signalized Intersections, Energy Optimized Solution, Connected and Automated Vehicles.
Abstract:
This study implements and tests an Eco-Cooperative Adaptive Cruise Control at Intersections (Eco-CACC-I) system in a large-scale metropolitan network to quantify the system-level performance considering different vehicle powertrains, connected automated vehicle (CAV) market penetration rates, and congestion levels. Specifically, three vehicle powertrains are considered in this study, including internal combustion engine vehicles (ICEVs), battery electric vehicles (BEVs) and hybrid electric vehicles (HEVs). This study integrates the Eco-CACC-I controller with different fuel/energy consumption models, so that the controller can compute energy-optimized solutions to assist ICEVs, BEVs and HEVs traverse signalized intersections. A simulated traffic network in the Greater Los Angeles Area including the downtown LA and the immediate vicinity is used to implement and test the Eco-CACC-I controller. In particular, 1,606 arterial links that are either directly upstream or downstream 457 coord
inated adaptive traffic signal controllers are used to test the Eco-CACC-I controller. The test results demonstrate that the controller produces positive impacts on saving fuel/energy consumption, reducing travel time and delays on urban networks for different combinations of CAV market penetration and congestion levels.
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